class_docstr: The Xception backobne of DeepLabv3+ implementation based on PaddlePaddle.
  
  The original article refers to
   Liang-Chieh Chen, et, al. "Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation"
   (https://arxiv.org/abs/1802.02611)
  
   Args:
       backbone (str): Which type of Xception_DeepLab to select. It should be one of ('xception_41', 'xception_65', 'xception_71').
       in_channels (int, optional): The channels of input image. Default: 3.
       pretrained (str, optional): The path of pretrained model.
       output_stride (int, optional): The stride of output features compared to input images. It is 8 or 16. Default: 16.
code: def init_weight(self):
      if self.pretrained is not None:
          utils.load_pretrained_model(self, self.pretrained)
  
imports: import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
  from paddleseg.models import layers
label_desc: Use image node_id 3 for calling the XceptionDeeplab obj's underlying member method code with example usage: obj.init_weight() without return types